DNA-based therapy has made tremendous advances recently, as evident by the increase in emerging potential therapies such as gene replacement and antisense oligonucleotides to alter splicing or downregulate an extra allele. These therapies hold the promise to treat many IDDs; however, major challenges must be addressed to achieve successful clinical trials. Safety of such therapies is of the utmost importance since many of the genes are dosage sensitive. It is therefore critical to identify outcome measures sensitive to target engagement and able to detect overtreatment and unintended conversion of gain-of-function phenotypes into a loss-of-function phenotypes, and vice versa. Here, we focus on MECP2- (Rett vs. MECP2 Duplication), RAI1- (Smith-Magenis vs. Potocki-Lupski syndrome) and SHANK3- (Phelan-McDermid vs. SHANK3 Duplication) associated disorders as test cases of IDDs that are caused by alterations of these dosage-dependent genes. We propose to identify molecular and neurocircuitry mediators/effectors of dosage alterations of these genes, both peripherally and centrally, to develop composite biomarkers that are responsive to gene dosage in each individual at their particular disease stage. Toward this goal, we capitalize on the established patient cohorts at Baylor College of Medicine, which has an extensive history in studying these disorders and their genetics. In Aim 1, we will establish patient-specific molecular signatures of human induced neurons (iNs), derived from both fibroblasts and inducible pluripotent stem cells, and blood, using metabolomics and transcriptomics. In Aim 2, we will establish patient-specific autonomic and sensory neurocircuitry signatures of the momentary disease stage and severity using novel pre-pulse inhibition paradigm, pupillometry, and evoked potentials. These signatures will be obtained twice from the same subject, 8-12 months apart, to assess stability. We will then integrate these dense multimodal datasets from each subject to generate a composite biomarker that accurately represents personalized response to the gene dosage level at that particular time. In contrast to conventional population studies ? and in the spirit of precision medicine ? this analysis framework relies on complete and diverse datasets from each participant because safety at the individual level is paramount to avoid causing unintended phenotypes. This project is possible because of the ability to access the innovative services from all the cores. The strategies we develop will provide a template to advance the use of DNA-based therapy for treatment of many monogenic disorders and could help inform many disorders that are gene dosage- dependent. The patient-specific cell lines, molecular, and circuit data will be available for the scientific community in perpetuity, will complement natural history studies, and will inform future clinical trials. Lastly, the new methodologies for examining neurocircuitry and the integrative data analysis approaches at multiple levels will potentially provide transformative tools and analytical algorithms for assessment, safe dosing, and accelerated clinical trials for multiple gene dosage-dependent IDDs.